This paper proposes an optimum link weight assignment methodology for structurally controllable complex networks. The networks can be represented by intricate graphs. The graphs along with their flexible links, which need to be properly designed, can be regarded as high order integrated multi-agent systems. The work has been carried out for optimal assignment of link weights of a graph and the optimization technique is based on an intelligent algorithm inspired by the nature, namely the Bacterial foraging algorithm (Bact-for). Further, we have established the fact that a graphs/networks with optimal link weights result in a strong structurally controllable networks, which when exited with a suitable inputs, would behave as completely state-controlled systems. Incidentally, Bact-for is emerging as a robust and a competitive solution tool for multi-agent optimization kind of problems and that is quite well-suited for distributed control and optimization domain. The performance of the proposed method of optimization has been compared with another well-known evolutionary approach for solving multi-optimization kind of problems, namely Particle swarm optimization with inertia weight (PSO-IW). Though both the evolutionary methods have their own merits and demerits, in our case, the simulation results, clearly show that Bact-for emerges out to be the superior one.